Periodontitis is a polymicrobial infection that causes destruction of tooth-supporting structures and results in tooth loss. 41.9% of periodontitis is attributable to smoking; and with 1.2 billion adults worldwide currently smoking, this disease presents a global public health issue. Subgingival bacteria are known to play an important role in disease pathogenesis; however, the effects of smoking on this community are poorly understood. Our goal is to test the hypothesis that smoking preferentially enriches this polymicrobial ecosystem for pathogenic organisms at the expense of health-compatible species. Our strategy is to combine unique, large-scale clinical studies with robust, high-throughput molecular assays, computational phylogenetics and bioinformatics for a comprehensive exploration of the subgingival microbiome. This approach will bridge the gap between clinical outcome-based studies and in vitro investigations using bacterial cultures and artificially developed biofilms. We will initially combine a cross-sectional study design with deep sequencing of 16S rRNA genes to identify bacteria associated with smoking-related periodontitis. We will then explore the compositional responses of the subgingival biofilm to smoking cessation by combining a longitudinal clinical study with deep sequencing. We will use a targeted, quantitative molecular assay to explore the salivary microbiome for disease markers and predictors. The proposed studies will bring us closer to understanding the role of smoking in the pathogenesis of periodontitis, provide biologically-validated timelines for administering periodontal therapy to patients following smoking cessation, and develop salivary indicators or predictors of disease.